Risk assessment of the use of sub-optimal levels of weak-acid preservatives in the control of mould growth on bakery products

Abstract

The hurdle technology approach was used to prevent fungal growth of common contaminants of bakery products including isolates belonging to the genera Eurotium, Aspergillus and Penicillium. Several levels (0.003%, 0.03% and 0.3%) of calcium propionate, potassium sorbate and sodium benzoate were assayed on a model agar system in a full-factorial experimental design in which the other factors assayed were pH (4.5, 6 and 7.5) and a_w (0.80, 085, 0.90 and 0.95). Potassium sorbate was found to be the more suitable preservative to be used in combination with the common levels of pH and a_w in Spanish bakery products. Sub-optimal concentrations (0.003% and sometimes 0.03%) led to an enhancement of fungal growth. None of the preservatives had a significant inhibitory effect at neutral pH.

Introduction

Mould growth on bakery products during storage is a serious economic problem. Because of the water activity of these products (0.75–0.90 a_w), spoilage moulds are commonly xerophilic, Eurotium and Aspergillus species. Moulds are destroyed during baking and contamination arises from mould spores derived from atmosphere or from surfaces during the cooling, finishing and wrapping procedures (Seiler, 1988).

In the last few years, the bakery products and flour confectionery sector has witnessed intense technological progress which has brought many changes in process innovation, and in commercial and qualitative characteristics of the products. Usually, bakery products are packaged in plastic films after baking and cooling, and they are consumed within 1 or 2 months (Ponte and Tsen, 1987).

Hurdle technology is now widely used in the design of new food products (Leistner, 1992). Hurdle technology combined with predictive microbiology may be the most suitable tool to develop new and safe products. The main variables to be considered in predictive microbiology for bakery products design must include a_w and pH, as well as others such as atmosphere composition in the package, concentration of preservatives, storage temperature, etc.

Weak organic acids such as propionic, benzoic and sorbic are used as hurdles in food preservation. The antimicrobial activity of these weak acids is mainly dependent upon the undissociated molecule Eklund, 1983, Eklund, 1985, Pethybridge et al., 1983. A reduction of pH from 6.0 to 5.0–5.2 results in a large relative increase in the proportion of the undissociated form (Chirife and Favetto, 1992). However, the modern trend is to reduce the concentration of preservatives in foodstuffs due to consumer demands.

The range of microorganisms used in this study represents the typical mycoflora of Spanish bakery products consisting of xerophilic species of Eurotium, Aspergillus and Penicillium. The a_w of these products varies between 0.70 and 0.85 approximately. Many Aspergillus species are xerophilic and capable of growing on media containing high concentrations of salt or sugar (Pitt and Hocking, 1997). Most xerophiles grow best between 22 and 25 °C (Beuchat and Hocking, 1990). Bakery products are kept at room temperature, conditions under which xerophiles grow optimally.

Spanish bakery products have pH values ranging from 4.3 (ensaimada) to 8.8 (magdalenas) (Abellana et al., 1997). The optimal pH for growth of most xerophiles is from 6.5 to 6.8 (Beuchat and Hocking, 1990). Some products spoil before the expiry date, and the most likely cause is condensation of moisture on the surface of the cakes after packing, if they have not been cooled enough. A recent study on bakery products (Abellana et al., 1999a) highlights the importance of a_w and storage temperature on the growth of Eurotium species.

The objectives of the present work were (i) to study the suitability of using both standard and sub-optimal concentrations of weak-acid preservatives to prevent the growth of common bakery products contaminants (the hurdle technology concept was applied by combining pH, a_w and preservatives as hurdles) and (ii) to develop predictive models from the data as tools for product design.